class_docstr: Dataset of penguin tabular data.
  
  From https://www.tensorflow.org/datasets/catalog/penguins.
code: def __init__(self, max_examples: Optional[int] = None):
      peng = tfds.load("penguins/simple", download=True, try_gcs=True)
      dataset_df = tfds.as_dataframe(peng["train"])
  
      # Filter out invalid rows.
      dataset_df = dataset_df.loc[dataset_df["sex"] != 2]
      records = dataset_df.to_dict(orient="records")
      self._examples = [
          PenguinDataset.lit_example_from_record(rec) for rec in records
      ][:max_examples]
  
file_path: lit/lit_nlp/examples/datasets/penguin_data.py
imports: from collections.abc import Mapping
  from typing import Optional, Union
  from lit_nlp.api import dataset
  from lit_nlp.api import types
  import tensorflow_datasets
label_desc: Use image node_id 2 to create a new PenguinDataset object from inherited base classes: lit_dataset with example: obj = PenguinDataset(max_examples)